Title page for ETD etd-32498-143727

A Heuristic Nonlinear Constructive Method for Electric
Power Distribution System Reconfiguration

Degree

PhD

Department

Electrical Engineering

Advisory Committee

Advisor Name

Title

Broadwater, Robert P.

Committee Chair

Cyre, Walling R.

Committee Member

Herdman, Terry L.

Committee Member

Liu, Yilu

Committee Member

VanLandingham, Hugh F.

Committee Member

Keywords

Loss Minimization

Power Distribution Control

Power Distribution Planning

Date of Defense

1998-04-23

Availability

unrestricted

Abstract

The electric power distribution system usually operates
a radial configuration, with tie switches between circuits
to provide alternate feeds. The losses would be minimized
if all switches were closed, but this is not done because
it complicates the system's protection against overcurrents.
Whenever a component fails, some of the switches must be
operated to restore power to as many customers as possible.
As loads vary with time, switch operations may reduce losses
in the system. Both of these are applications for
reconfiguration.

The problem is combinatorial, which precludes algorithms
that guarantee a global optimum. Most existing
reconfiguration algorithms fall into two categories. In
the first, branch exchange, the system operates in a
feasible radial configuration and the algorithm opens and
closes candidate switches in pairs. In the second, loop
cutting, the system is completely meshed and the algorithm
opens candidate switches to reach a feasible radial
configuration. Reconfiguration algorithms based on
linearized transshipment, neural networks, heuristics,
genetic algorithms, and simulated annealing have also been
reported, but not widely used. These existing
reconfiguration algorithms work with a simplified model of
the power system, and they handle voltage and current
constraints approximately, if at all.

The algorithm described here is a constructive method,
using a full nonlinear power system model that accurately
handles constraints. The system starts with all switches
open and all failed components isolated. An optional
network power flow provides a lower bound on the losses.
Then the algorithm closes one switch at a time to minimize
the increase in a merit figure, which is the real loss
divided by the apparent load served. The merit figure
increases with each switch closing. This principle, called
discrete ascent optimal programming (DAOP), has been applied
to other power system problems, including economic dispatch
and phase balancing. For reconfiguration, the DAOP method's
greedy nature is mitigated with a backtracking algorithm.
Approximate screening formulas have also been developed for
efficient use with partial load flow solutions. This method's
main advantage is the accurate treatment of voltage and
current constraints, including the effect of control action.
One example taken from the literature shows how the
DAOP-based algorithm can reach an optimal solution, while
adjusting line voltage regulators to satisfy the voltage
constraints.